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Precise determination of thermodynamic parameters in ultracold Bose gases remains challenging due to the destructive nature of conventional measurement techniques and inherent experimental uncertainties. We demonstrate a machine learning…

Quantum Gases · Physics 2025-10-29 Jack Griffiths , Steven A. Wrathmall , Simon A. Gardiner

Tungsten (W) is the leading candidate material for plasma-facing components in fusion reactors, yet its upper operational temperature is limited by premature grain growth and recrystallization processes. Irradiation adds further…

Materials Science · Physics 2026-02-23 Jinxin Yu , Sicong He , Giacomo Po , Jason R. Trelewicz , Timothy J. Rupert , Jaime Marian

The goal of this report is to present the final project conducted in order to fulfill the requirements of the M.Sc. degree at the Department of Mechanical Engineering, Ben-Gurion University (BGU) of the Negev. The project comprises…

Fluid Dynamics · Physics 2022-12-29 Dmitry Zviaga

In nuclear fusion reactors, tungsten will be exposed to high neutron loads at high temper atures (>900 C). The evolution and degradation of the mechanical properties under these conditions is uncertain and therefore constitutes a major…

Materials Science · Physics 2019-01-11 A. Mannheim , J. A. W. van Dommelen , M. G. D. Geers

Molecular dynamics simulations have been performed to understand the influence of temperature on the tensile deformation and fracture behavior of $<$111$>$ BCC Fe nanowires. The simulations have been carried out at different temperatures in…

Materials Science · Physics 2017-10-09 G. Sainath , B. K. Choudhary

We show that machine learning can improve the accuracy of simulations of stress waves in one-dimensional composite materials. We propose a data-driven technique to learn nonlocal constitutive laws for stress wave propagation models. The…

Machine Learning · Computer Science 2020-12-09 Huaiqian You , Yue Yu , Stewart Silling , Marta D'Elia

Advanced tensor decomposition, such as Tensor train (TT) and Tensor ring (TR), has been widely studied for deep neural network (DNN) model compression, especially for recurrent neural networks (RNNs). However, compressing convolutional…

Computer Vision and Pattern Recognition · Computer Science 2021-07-28 Miao Yin , Yang Sui , Siyu Liao , Bo Yuan

Ultracold quantum gases are highly controllable and, thus, capable of simulating difficult quantum many-body problems ranging from condensed matter physics to astrophysics. Although experimental realizations have so far been restricted to…

Quantum Gases · Physics 2022-02-17 Andrea Tononi , Axel Pelster , Luca Salasnich

The Multi-Mode Model (MMM) for turbulent transport was applied to a large set of well-analyzed discharges from the National Spherical Torus Experiment (NSTX) in order to evaluate its sensitivities to a wide range of plasma conditions. MMM…

Constitutive laws relate fluid stress to deformation and underpin predictions of non-Newtonian behavior in industrial and biological fluids. Standard characterization relies on measurements in idealized flows that often miss physics…

Molecular dynamics simulations are widely used to investigate nucleation in first-order phase transitions. Brute-force simulations, though popular, are limited to conditions of high metastability, where the critical cluster and the…

Chemical Physics · Physics 2026-02-10 Thomas Philippe , Yijian Wu , Aymane Graini

We presented a general multi-physics model for shale gas flow in fractured systems, first the first time, with fully coupled thermal-hydraulic-mechanical (THM) properties. The impact of gas adsorption, real gas properties, gas flow in…

Geophysics · Physics 2017-11-08 HanYi Wang

The 100 MW cryogenic liquid oxygen/hydrogen multi-injector combustor BKD operated by the DLR Institute of Space Propulsion is a research platform that allows the study of thermoacoustic instabilities under realistic conditions,…

SAM, a plant-level system analysis tool for advanced reactors (SFR, LFR, MSR/FHR) is under development at Argonne. As a modern system code, SAM aims to improve the predictions of 3D flows relevant to reactor safety during transient…

Fluid Dynamics · Physics 2020-05-04 Yangmo Zhu , Nam Dinh , Rui Hu , Adam Kraus

Accurate prediction of hydrogen sorption in fine-grained geological materials is essential for evaluating underground hydrogen storage capacity, assessing caprock integrity, and characterizing hydrogen migration in subsurface energy…

Machine Learning · Computer Science 2026-03-31 Mohammad Nooraiepour , Mohammad Masoudi , Zezhang Song , Helge Hellevang

The fusion probability for the production of superheavy nuclei in cold fusion reactions was investigated and compared with recent experimental results for $^{48}$Ca, $^{50}$Ti, and $^{54}$Cr incident on a $^{208}$Pb target. Calculations…

Nuclear Theory · Physics 2022-05-25 T. Cap , M. Kowal , K. Siwek-Wilczyńska

A self-consistent description for hot $\Lambda$ hypernuclei in hypothetical big boxes is developed within the relativistic Thomas-Fermi approximation in order to investigate directly the liquid-gas phase coexistence in strangeness finite…

Nuclear Theory · Physics 2016-11-30 Jinniu Hu , Zhaowen Zhang , Shishao Bao , Hong Shen

Temperature field prediction is of great importance in the thermal design of systems engineering, and building the surrogate model is an effective way for the task. Generally, large amounts of labeled data are required to guarantee a good…

Machine Learning · Computer Science 2023-01-18 Yunyang Zhang , Zhiqiang Gong , Weien Zhou , Xiaoyu Zhao , Xiaohu Zheng , Wen Yao

Atomic layer deposition allows for precise control over film thickness and conformality. It is a critical enabler of high aspect ratio structures, such as 3D NAND memory, since its self-limiting behavior enables higher conformality than…

Heat pump systems are critical components in modern energy-efficient buildings, yet their operational stress detection remains challenging due to complex thermodynamic interactions and limited real-world data. This paper presents a novel…

Machine Learning · Computer Science 2025-12-17 Md Shahabub Alam , Md Asifuzzaman Jishan , Ayan Kumar Ghosh